Abstract
Purpose. To describe the procedure for performing kaolin deposit clustering in order to determine the regularities of the distribution of quality indicators, to distinguish promising areas and to calculate the volumes of minerals of different conditions. Methodology. Implementation of systematization, analysis and statistical processing of the results of geological research of the deposit. Identification of criteria for evaluating the qualitative properties of a mineral. Performing interpolation based on the results of geological studies in order to establish the qualitative indicators of the mineral and the regularities of their distribution within the deposit. Justification of the feasibility of using the method of inverse distances weighting to achieve the set goals. Performing deposit clustering and calculating the volume of reserves of different conditions. Results. The main result of deposit clustering is the direct identification of areas within which the secondary conditions of the mineral are located. The results of clustering allow: to display the content of constituent components in the contours of the deposit; identify promising areas for development; to determine the optimal direction of expansion of the mining operations front; determine the optimal location of overburden mining; calculate the volumes of minerals within the deposit under different trademarks; average the mining mass in order to improve its quality. Scientific novelty. The systematization and review of the existing methods of geometrization of mineral deposits has been carried out. The expediency of using the interpolation method to geometrize the complex structure of the Yosypiv deposit of primary kaolin has been investigated empirically. The expediency of using such a method has been substantiated, and the relevance of the obtained results has been assessed. Practical significance. The results obtained during the research make it possible to optimize the design process of a kaolin mining enterprise by obtaining a detailed and visual distribution of the deposit into clusters in accordance with the desired qualitative indicators: mineral composition, chemical composition, physical and mechanical indicators, etc. At the same time, the obtained results make it possible to predict the patterns of distribution of various types of properties within the deposit and to estimate the overall economic effect of its development with a higher degree of accuracy.
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